Along with an increasing availability of “intelligent” unmanned agents, trends in systems development are increasingly teaming humans with unmanned teammates to function across complex domains. Teaming humans with unmanned teammates may offer a variety of benefits, such as: reducing overall manned initiatives; reducing total human decision time in the course of a mission; and, flexible adaptation to dynamic and uncertain complexity in operational environments.
While effective human-human teams typically begin by developing highly efficient communication and decision mechanisms that promote the judicious engagement of other human teammates, a similar development in human-unmanned teammates is largely unrealized. In an operational setting, a team may comprise a single human operator (hereinafter, “human operator” is referred to as “human” for simplicity) that is responsible for a series of tasks and also responsible to be a mission manager for multiple unmanned teammates. Over the course of a mission, one or more of the unmanned teammates (referred to herein as unmanned agents (UAs)) may request human engagement on a mission task. In operational settings such as this, the attention or engagement of the human is limited and is one of the most valuable resources of the mission. Therefore, culling and prioritizing the requests for human engagement is necessary for highly efficient human-UA communication.
Accordingly, a method and system for determining whether, when, and how an unmanned agent interrupts a human is desirable. The desired method and system uses a two-step multivariate analysis to (i) process a request for human interaction to determine whether to interrupt a human, and (ii) if it determined to interrupt the human, to determine when and how to interrupt the human. The desired method and system interrupts the human in a manner that reflects analysis of variables such as mission criticality, whether a delay in the mission is acceptable, and the propriety of interrupting the human.